Cargando…

Estimating cell type-specific differential expression using deconvolution

Detalles Bibliográficos
Autores principales:	Jaakkola, Maria K, Elo, Laura L
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Oxford University Press 2021
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769698/ https://www.ncbi.nlm.nih.gov/pubmed/34651640 http://dx.doi.org/10.1093/bib/bbab433

Ejemplares similares

Computational deconvolution to estimate cell type-specific gene expression from bulk data
por: Jaakkola, Maria K, et al.
Publicado: (2021)

Comparison of methods to detect differentially expressed genes between single-cell populations
por: Jaakkola, Maria K, et al.
Publicado: (2017)

Disease-specific classification using deconvoluted whole blood gene expression
por: Wang, Li, et al.
Publicado: (2016)

DEBay: A computational tool for deconvolution of quantitative PCR data for estimation of cell type-specific gene expression in a mixed population
por: Devaraj, Vimalathithan, et al.
Publicado: (2020)

Deconvoluting kernel density estimation and regression for locally differentially private data
por: Farokhi, Farhad
Publicado: (2020)

Empirical comparison of structure-based pathway methods
por: Jaakkola, Maria K., et al.
Publicado: (2016)

Exon-level estimates improve the detection of differentially expressed genes in RNA-seq studies
por: Mehmood, Arfa, et al.
Publicado: (2021)

Improving sensitivity of linear regression-based cell type-specific differential expression deconvolution with per-gene vs. global significance threshold
por: Glass, Edmund R., et al.
Publicado: (2016)

Deconvolution algorithms for inference of the cell-type composition of the spatial transcriptome
por: Zhang, Yingkun, et al.
Publicado: (2022)

Deconvolution reveals cell-type-specific transcriptomic changes in the aging mouse brain
por: Ren, Yingxue, et al.
Publicado: (2023)

De novo compartment deconvolution and weight estimation of tumor samples using DECODER
por: Peng, Xianlu Laura, et al.
Publicado: (2019)

ESHRD: deconvolution of brain homogenate RNA expression data to identify cell-type-specific alterations in Alzheimer’s disease
por: Piras, Ignazio S., et al.
Publicado: (2020)

Deconvolution of Human Brain Cell Type Transcriptomes Unraveled Microglia-Specific Potential Biomarkers
por: Ayana, R., et al.
Publicado: (2018)

Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis
por: Chen, Yanshuo, et al.
Publicado: (2022)

ROTS: reproducible RNA-seq biomarker detector—prognostic markers for clear cell renal cell cancer
por: Seyednasrollah, Fatemeh, et al.
Publicado: (2016)

ADAPTS: Automated deconvolution augmentation of profiles for tissue specific cells
por: Danziger, Samuel A., et al.
Publicado: (2019)

Single-Cell Approaches to Deconvolute the Development of HSCs
por: Xiang, Yang, et al.
Publicado: (2021)

Accurate estimation of rare cell type fractions from tissue omics data via hierarchical deconvolution
por: Huang, Penghui, et al.
Publicado: (2023)

Bulk tissue cell type deconvolution with multi-subject single-cell expression reference
por: Wang, Xuran, et al.
Publicado: (2019)

Spatial Transcriptomic Cell-type Deconvolution Using Graph Neural Networks
por: Li, Yawei, et al.
Publicado: (2023)

Deconvolution of cell type-specific drug responses in human tumor tissue with single-cell RNA-seq
por: Zhao, Wenting, et al.
Publicado: (2021)

Cell-type deconvolution from DNA methylation: a review of recent applications
por: Titus, Alexander J., et al.
Publicado: (2017)

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes
por: Jeong, Yunhee, et al.
Publicado: (2022)

Cell-type deconvolution of bulk RNA-Seq from kidney using opensource bioinformatic tools
por: Riojas, Angelica M., et al.
Publicado: (2023)

Benchmarking of cell type deconvolution pipelines for transcriptomics data
por: Avila Cobos, Francisco, et al.
Publicado: (2020)

Spatially Informed Cell Type Deconvolution for Spatial Transcriptomics
por: Ma, Ying, et al.
Publicado: (2022)

Gene expression deconvolution in clinical samples
por: Zhao, Yingdong, et al.
Publicado: (2010)

Motor Nerve Conduction Block Estimation in Demyelinating Neuropathies by Deconvolution
por: Mesin, Luca, et al.
Publicado: (2022)

Placental cell type deconvolution reveals that cell proportions drive preeclampsia gene expression differences
por: Campbell, Kyle A., et al.
Publicado: (2023)

imply: improving cell-type deconvolution accuracy using personalized reference profiles
por: Meng, Guanqun, et al.
Publicado: (2023)

Hierarchical deconvolution for extensive cell type resolution in the human brain using DNA methylation
por: Zhang, Ze, et al.
Publicado: (2023)

scMD: cell type deconvolution using single-cell DNA methylation references
por: Cai, Manqi, et al.
Publicado: (2023)

BuDDI: Bulk Deconvolution with Domain Invariance to predict cell-type-specific perturbations from bulk
por: Davidson, Natalie R., et al.
Publicado: (2023)

Molecular characterization and cell type composition deconvolution of fibrosis in NAFLD
por: Pantano, Lorena, et al.
Publicado: (2021)

Enhanced differential expression statistics for data-independent acquisition proteomics
por: Suomi, Tomi, et al.
Publicado: (2017)

Bayesian-based deconvolution fluorescence microscopy using dynamically updated nonstationary expectation estimates
por: Wong, Alexander, et al.
Publicado: (2015)

Single-cell Bayesian deconvolution
por: Torregrosa-Cortés, Gabriel, et al.
Publicado: (2023)

Probe-level estimation improves the detection of differential splicing in Affymetrix exon array studies
por: Laajala, Essi, et al.
Publicado: (2009)

PASI: A novel pathway method to identify delicate group effects
por: Jaakkola, Maria K., et al.
Publicado: (2018)

ROTS: An R package for reproducibility-optimized statistical testing
por: Suomi, Tomi, et al.
Publicado: (2017)

Cannot write session to /tmp/vufind_sessions/sess_fbcpetm9ancjd4tvorhiglslsg